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Ovarian cancer patients frequently develop resistance to chemotherapy regiments utilizing Taxol and carboplatin. One of the resistance factors that protects cancer cells from Taxol-based therapy is multi-drug resistance 1 (MDR1). micro(mi)RNAs are small noncoding RNAs that negatively regulate protein expression. Members of the let-7 family of miRNAs are downregulated in many human cancers, and low let-7 expression has been correlated with resistance to microtubule targeting drugs (Taxanes), although little is known that would explain this activity. We now provide evidence that, while let-7 is not a universal sensitizer of cancer cells to Taxanes, it affects acquired resistance of cells to this class of drugs by targeting IMP-1, resulting in de-stabilization of the mRNA of MDR1. Introducing let-7g into ADR-RES cells expressing both IMP-1 and MDR1 reduced expression of both proteins rendering the cells more sensitive to treatment with either Taxol or vinblastine without affecting the sensitivity of the cells to carboplatin, a non-MDR1 substrate. This effect could be reversed by reintroducing IMP-1 into let-7g high/MDR1 low cells causing MDR1 to again become stabilized. Consistently, many relapsed ovarian cancer patients tested before and after chemotherapy were found to downregulate let-7 and to co-upregulate IMP-1 and MDR1, and the increase in the expression levels of both proteins after chemotherapy negatively correlated with disease-free time before recurrence. Our data point at IMP-1 and MDR1 as indicators for response to therapy, and at IMP-1 as a novel therapeutic target for overcoming multidrug resistance of ovarian cancer.

Recent miRNA transfection experiments show strong evidence that miRNAs influence not only their target but also non-target genes; the precise mechanism of the extended regulatory effects of miRNAs remains to be elucidated. A hypothetical two-layer regulatory network in which transcription factors (TFs) function as important mediators of miRNA-initiated regulatory effects was envisioned, and a comprehensive strategy was developed to map such miRNA-centered regulatory cascades. Given gene expression profiles after miRNA-perturbation, along with putative miRNA-gene and TF-gene regulatory relationships, highly likely degraded targets were fetched by a non-parametric statistical test; miRNA-regulated TFs and their downstream targets were mined out through linear regression modeling. When applied to 53 expression datasets, this strategy discovered combinatorial regulatory networks centered around 19 miRNAs. A tumor-related regulatory network was diagrammed as an example, with the important tumor-related regulators TP53 and MYC playing hub connector roles. A web server is provided for query and analysis of all reported data in this article. Our results reinforce the growing awareness that non-coding RNAs may play key roles in the transcription regulatory network. Our strategy could be applied to reveal conditional regulatory pathways in many more cellular contexts.

Objects Our objective was to develop an oligonucleotide DNA microarray (OMA) for genome-wide microRNA profiling and use this method to find miRNAs, which control organic development especially for nervous system. Materials and methods Eighteen organic samples included cerebrum and spinal cord samples from two aborted human fetuses. One was 12 gestational weeks old (G12w) and the other was 24 gestational weeks old (G24w). Global miRNA expression patterns of different organs were investigated using OMA and Northern blot. Conclusion The OMA revealed that 72–83% of miRNAs were expressed in human fetal organs. A series of microRNAs were found specifically and higher-expressed in the human fetal nervous system and confirmed consistently by Northern blot, which may play a critical role in nervous system development.

MicroRNAs (miRNAs) are a group of RNAs that play important roles in regulating gene expression and protein translation. In a previous study, we established an oligonucleotide microarray platform to detect miRNA expression. Because it contained only hundreds of probes, data normalization was difficult. In this study, the microarray data for eight miRNAs extracted from inflamed rat dorsal root ganglion (DRG) tissue were normalized using 15 methods and compared with the results of real-time polymerase chain reaction. It was found that the miRNA microarray data normalized by the print-tip loess method were the most consistent with results from real-time polymerase chain reaction. Moreover, the same pattern was also observed in 14 different types of rat tissue. This study compares a variety of normalization methods and will be helpful in the preprocessing of miRNA microarray data.

Background MicroRNAs (miRNAs) are a large group of RNAs that play important roles in regulating gene expression and protein translation. Several studies have indicated that some miRNAs are specifically expressed in human, mouse and zebrafish tissues. For example, miR-1 and miR-133 are specifically expressed in muscles. Tissue-specific miRNAs may have particular functions. Although previous studies have reported the presence of human, mouse and zebrafish tissue-specific miRNAs, there have been no detailed reports of rat tissue-specific miRNAs. In this study, Home-made rat miRNA microarrays which established in our previous study were used to investigate rat neural tissue-specific miRNAs, and mapped their target genes in rat tissues. This study will provide information for the functional analysis of these miRNAs. Results In order to obtain as complete a picture of specific miRNA expression in rat neural tissues as possible, customized miRNA microarrays with 152 selected miRNAs from miRBase were used to detect miRNA expression in 14 rat tissues. After a general clustering analysis, 14 rat tissues could be clearly classified into neural and non-neural tissues based on the obtained expression profiles with p values < 0.05. The results indicated that the miRNA profiles were different in neural and non-neural tissues. In total, we found 30 miRNAs that were specifically expressed in neural tissues. For example, miR-199a was specifically expressed in neural tissues. Of these, the expression patterns of four miRNAs were comparable with those of Landgraf et al., Bak et al., and Kapsimani et al. Thirty neural tissue-specific miRNAs were chosen to predict target genes. A total of 1,475 target mRNA were predicted based on the intersection of three public databases, and target mRNA's pathway, function, and regulatory network analysis were performed. We focused on target enrichments of the dorsal root ganglion (DRG) and olfactory bulb. There were four Gene Ontology (GO) functions and five KEGG pathways significantly enriched in DRG. Only one GO function was significantly enriched in the olfactory bulb. These targets are all predictions and have not been experimentally validated. Conclusion Our work provides a global view of rat neural tissue-specific miRNA profiles and a target map of miRNAs, which is expected to contribute to future investigations of miRNA regulatory mechanisms in neural systems.